Natural Language Processing in Healthcare
The healthcare sector is nowadays relying on advanced technologies to process large amounts of data. One such exciting development is the use of natural language processing (NLP), where machines process human-generated data, like text or speech. Advanced in NLP and its integration into healthcare can provide a way to translate human language as actionable data.
NLP is a transformative element in EHR systems, where the primary function is to turn big data into smart data, by ingesting speech text and other forms of data to make it sensible. This helps healthcare providers gain actionable insights turning invaluable information into accessible ones.
Osiz, as a leading AI Development Company leverages NLP in the healthcare industry to meet technology and healthcare providers at a growing pace. We integrate natural language processing solutions into healthcare with AI-powered technology to provide sufficient, high-quality data to help in the medical struggle.
Our Natural Language Processing Services in Healthcare
Extracting Data from Human Speech
Some clinicians and researchers need information about clinical notes, patient-reported data, notes from patient phone calls, and telehealth transcripts. Our advanced NLP algorithms make this kind of data transparent and accessible. We combine NLP with machine learning and predictive analytics for healthcare providers to identify the correct medical and social interventions.
Making Sense of Unstructured Data
Unstructured data like text files, images, transcripts, chat conversations, and recordings, lacks predefined models. With 80% of health data is unstructured, the impact on health outcomes and care delivery is enormous if data is being accessed and organized. Our NLP services transform unstructured data into structured, improving patient care and health outcomes.
NLP Use Cases and Applications
- Speech Recognition: Chatbots, voice assistants, and real-time transcription delivered as EHRs, for patient access.
- Clinical Documentation: Health history and physician notes are simplified as documents to improve record accuracy.
- NLP-Driven Coding: Computer-assisted coding (CAC) is used in medical codes from clinical documentation.
- Automated Registry Reporting: EHRs are used to map text to structured fields enabling pattern recognition and information extraction.
- Clinical Decision Support: It aids in grouping text classifications and extracting information from patient inputs.
- Predictive Analytics: Valuable predictive data is gained from unstructured healthcare information, improving prediction results.
- Phenotyping and Biomarker Discovery: Record accuracy and patient safety is improved by computational phenotyping and biomarker discovery.
- Interpreting Handwritten Notes: EHRs convert handwritten notes into useful data promising no critical information is lost.
Benefits of NLP in Healthcare
Healthcare providers can expect:
- Good quality of care.
- Better patient and provider relationships.
- Improved patient health awareness.
Why Osiz for NLP in Healthcare?
Natural language processing in medicine has improved healthcare delivery and patient experience. EHR systems with NLP-powered algorithms can be a good investment. At Osiz, our experts program software solutions with natural language processing to analyze structured and unstructured data.
Our solutions are able to mine web data, business data repositories, and audio sources to detect current trends, and also we use predictive analytics capabilities. To successfully deploy NLP in healthcare, we are your trusted machine learning company who have 15 years of experience in this field and a great team of 500+ experts. We create custom NLP models with standard format and you can avail a free demo before the start.
